suggest_links

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden. It discloses key behavioral traits: 'Deterministic' and 'precision FLOOR,' which sets expectations for output quality/scope. It also notes the limitation (string matching only) and directs the model to supplement with another tool. However, it does not specify the exact return format or potential errors, so a small gap remains.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, no fluff. The first sentence delivers the core purpose immediately; the second provides essential guidance. Every sentence earns its place, and the structure is easy to parse.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple single-parameter tool with no output schema, the description covers purpose, usage, and even a cross-reference to a sibling tool. It does not specify the return format (e.g., entity IDs), but given the tool's simplicity and the strong usage guidance, it is nearly complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% and the single parameter already has a description in the schema ('Concept name and/or definition (the problem statement).'). The tool description adds no new parameter details beyond referencing 'the given statement,' which is consistent with the schema. Thus baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states exactly what the tool does: 'Deterministic candidates for what a concept measures: entities whose names phrase-match the given statement.' It uses a specific verb ('suggest') and resource ('links' as entities), and distinguishes itself from get_entity_catalogue by emphasizing deterministic phrase matching.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly instructs the model to 'additionally pick semantically related entities from get_entity_catalogue that string matching cannot find,' defining when to use this tool (for string matches) and when to use the alternative. This is clear and actionable guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.